Abstract

Samples of airborne particulate matter (PM2.5) were collected at a site in Lahore, Pakistan from November 2005 to January 2006. A total of 129 samples were collected using an Andersen Reference Ambient Air Sampler 2.5-400 sampler and analyzed for major ions, trace metals, and organic and elemental carbon concentrations. The data set was then analyzed by positive matrix factorization (PMF) to identify the possible sources of the atmospheric PM collected in this urban area. Six factors reproduced the PM2.5 sample compositions with meaningful physical interpretation of the resolved factors. The sources included secondary PM, diesel emissions, biomass burning, coal combustion, two-stroke vehicle exhaust, and industrial sources. Diesel and two-stroke vehicles contributed about 36%, biomass burning about 15%, and coal combustion sources around 13% of the PM2.5 mass. Nearly two thirds of the PM2.5 mass is carbonaceous material. Secondary particles contributed about 30% of PM2.5 mass. The conditional probability function (CPF) was then used to help identify likely locations of the sources present in this area. CPF analysis point to the east and northeast, which are directions of urban and industrial areas located across the border near Amritsar, India as the most probable source for high PM2.5 concentration from diesel and two-stroke vehicles exhaust in Lahore. Analysis of those days within three different ranges of PM2.5 concentration shows that most of the measured high PM2.5 mass concentrations were driven by diesel and two-stroke vehicle emissions including the associated primary sulfate. The use of the potential source contribution function (PSCF) to find the source locations of regionally transported particles is inapplicable in situations when high PM2.5 concentrations are dominated by local sources and local meteorology.

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